Examples of using Data volumes in English and their translations into Chinese
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Because such large data volumes are not easily processed, it is advantageous to average several thousand measuring points at a time.
As data volumes continue to grow and diversify, being able to make greater use of the information organizations are creating and capturing enhances competitive advantage.
In the case of big data, some organizations assume that“big” just means more transactions and large data volumes.
NetApp SnapRestore software uses stored Snapshot copies to recover entire file systems or data volumes in seconds.
In addition, they are used to control the capacity of servers, in order to be able to provide corresponding data volumes where required.
The team needed to find a new solution that could handle current data volumes and easily scale in the future.
For the National Center for Atmospheric Research's Computational and Information Services Laboratory(CISL), growing data volumes are part of its DNA.
With IoT and AI set to thrive over the next few years, data volumes will only increase.
Simply generating enormous amounts of data is not enough, these data volumes also have to be managed.
Before in-depth comparative analyses of large numbers of tests can be undertaken, the first requirement is efficient management of the data volumes that are acquired.
In addition, they are used to control the server capacities, in order to be able to provide corresponding data volumes if required.
Furthermore they are used for control of the server capacities to be able to provide corresponding data volumes in case of need.
The Duke production team now has a flexible, scalable platform that can accommodate changing requirements and growing data volumes well into the future.
In addition, such data are also utilized to control the server's capacity to be able to provide corresponding data volumes if needed.
The top three anticipated drivers of end-customer spending for 2016 are hybrid cloud, followed by network virtualization and increasing data volumes.
In addition, such data are also utilized to control the server's capacity to be able to provide corresponding data volumes if needed.
The data volumes can double every few months, and the data itself is complex- often in hundreds of different semi-structured and unstructured formats.
Today's database technology is becoming increasingly complex, and supports previously unthinkable data volumes- all driven by the demands of today's always-on economy.
Claburn(2017) indicates that the actions of the attackers on Hadoop based systems“may include destroying data nodes, data volumes, or snapshots with terabytes of data inseconds”.
This limitation will likely drive demand for new methodologies that can handle huge data volumes and complexities while also remaining transparent in decision making.